An Unsaturated Hydraulic Conductivity Model Based on the Capillary Bundle Model, the Brooks‐Corey Model and Waxman‐Smits Model

Soil unsaturated hydraulic conductivity (K), which depends on water content (θ) and matric potential (ψ), exhibits a high degree of variability at the field scale. Here we first develop a theoretical hydraulic‐electrical conductivity (σ) relationship under low and high salinity cases based on the ca...

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Veröffentlicht in:Water resources research 2023-06, Vol.59 (6), p.n/a
Hauptverfasser: Fu, Yongwei, Horton, Robert, Ren, Tusheng, Heitman, Joshua
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Ren, Tusheng
Heitman, Joshua
description Soil unsaturated hydraulic conductivity (K), which depends on water content (θ) and matric potential (ψ), exhibits a high degree of variability at the field scale. Here we first develop a theoretical hydraulic‐electrical conductivity (σ) relationship under low and high salinity cases based on the capillary bundle model and Waxman and Smits model which can account for the non‐linear behavior of σ at low salinities. Then the K‐σ relationship is converted into a K(θ, ψ) model using the Brooks‐Corey model. The model includes two parameters c and γ. Parameter c accounts for the variation of the term (λ + 2)/(λ + 4) where λ is the pore size distribution parameter in the Brooks‐Corey model, and the term m‐n where m and n are Archie's saturation and cementation exponents, respectively. Parameter γ is the sum of the tortuosity factor accounting for the differences between hydraulic and electrical tortuosity and Archie's saturation exponent. Based on a calibration data set of 150 soils selected from the UNSODA database, the best fitting log(c) and γ values were determined as −2.53 and 1.92, −4.39 and −0.14, −5.01 and −1.34, and −5.79 and −2.27 for four textural groups. The estimated log10(K) values with the new K(θ, ψ) model compared well to the measured values from an independent data set of 49 soils selected from the UNSODA database, with mean error (ME), relative error (RE), root mean square error (RMSE) and coefficient of determination (R2) values of 0.02, 8.8%, 0.80 and 0.73, respectively. A second test of the new K(θ, ψ) model using a data set representing 23 soils reported in the literature also showed good agreement between estimated and measured log10(K) values with ME of −0.01, RE of 9.5%, RMSE of 0.77 and R2 of 0.85. The new K(θ, ψ) model outperformed the Mualem‐van Genuchten model and two recently published pedo‐transfer functions. The new K(θ, ψ) model can be applied for estimating K under field conditions and for hydrologic modeling without need for soil water retention curve data fitting to derive a K function. Key Points A new unsaturated hydraulic conductivity model was developed in terms of independent θ and ψ values Best fitting values of two parameters in the new unsaturated hydraulic conductivity model were determined from 150 soils in the calibration data set The new model provided reliable estimates of hydraulic conductivity for 72 soils from two independent data sets
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Here we first develop a theoretical hydraulic‐electrical conductivity (σ) relationship under low and high salinity cases based on the capillary bundle model and Waxman and Smits model which can account for the non‐linear behavior of σ at low salinities. Then the K‐σ relationship is converted into a K(θ, ψ) model using the Brooks‐Corey model. The model includes two parameters c and γ. Parameter c accounts for the variation of the term (λ + 2)/(λ + 4) where λ is the pore size distribution parameter in the Brooks‐Corey model, and the term m‐n where m and n are Archie's saturation and cementation exponents, respectively. Parameter γ is the sum of the tortuosity factor accounting for the differences between hydraulic and electrical tortuosity and Archie's saturation exponent. Based on a calibration data set of 150 soils selected from the UNSODA database, the best fitting log(c) and γ values were determined as −2.53 and 1.92, −4.39 and −0.14, −5.01 and −1.34, and −5.79 and −2.27 for four textural groups. The estimated log10(K) values with the new K(θ, ψ) model compared well to the measured values from an independent data set of 49 soils selected from the UNSODA database, with mean error (ME), relative error (RE), root mean square error (RMSE) and coefficient of determination (R2) values of 0.02, 8.8%, 0.80 and 0.73, respectively. A second test of the new K(θ, ψ) model using a data set representing 23 soils reported in the literature also showed good agreement between estimated and measured log10(K) values with ME of −0.01, RE of 9.5%, RMSE of 0.77 and R2 of 0.85. The new K(θ, ψ) model outperformed the Mualem‐van Genuchten model and two recently published pedo‐transfer functions. The new K(θ, ψ) model can be applied for estimating K under field conditions and for hydrologic modeling without need for soil water retention curve data fitting to derive a K function. Key Points A new unsaturated hydraulic conductivity model was developed in terms of independent θ and ψ values Best fitting values of two parameters in the new unsaturated hydraulic conductivity model were determined from 150 soils in the calibration data set The new model provided reliable estimates of hydraulic conductivity for 72 soils from two independent data sets</description><identifier>ISSN: 0043-1397</identifier><identifier>EISSN: 1944-7973</identifier><identifier>DOI: 10.1029/2022WR034186</identifier><language>eng</language><publisher>Washington: John Wiley &amp; Sons, Inc</publisher><subject>capillary bundle model ; Cementation ; Curve fitting ; Datasets ; Electrical conductivity ; Electrical resistivity ; Hydraulic conductivity ; hydraulic conductivity model ; Hydraulics ; Hydrologic models ; Hydrology ; Mathematical models ; matric potential ; Modelling ; Moisture content ; Parameters ; Pore size ; Pore size distribution ; Root-mean-square errors ; Salinity ; Saturation ; Size distribution ; Soil ; Soil water ; Tortuosity ; Transfer functions ; Unsaturated soils ; Water content</subject><ispartof>Water resources research, 2023-06, Vol.59 (6), p.n/a</ispartof><rights>2023. The Authors.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). 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Here we first develop a theoretical hydraulic‐electrical conductivity (σ) relationship under low and high salinity cases based on the capillary bundle model and Waxman and Smits model which can account for the non‐linear behavior of σ at low salinities. Then the K‐σ relationship is converted into a K(θ, ψ) model using the Brooks‐Corey model. The model includes two parameters c and γ. Parameter c accounts for the variation of the term (λ + 2)/(λ + 4) where λ is the pore size distribution parameter in the Brooks‐Corey model, and the term m‐n where m and n are Archie's saturation and cementation exponents, respectively. Parameter γ is the sum of the tortuosity factor accounting for the differences between hydraulic and electrical tortuosity and Archie's saturation exponent. Based on a calibration data set of 150 soils selected from the UNSODA database, the best fitting log(c) and γ values were determined as −2.53 and 1.92, −4.39 and −0.14, −5.01 and −1.34, and −5.79 and −2.27 for four textural groups. The estimated log10(K) values with the new K(θ, ψ) model compared well to the measured values from an independent data set of 49 soils selected from the UNSODA database, with mean error (ME), relative error (RE), root mean square error (RMSE) and coefficient of determination (R2) values of 0.02, 8.8%, 0.80 and 0.73, respectively. A second test of the new K(θ, ψ) model using a data set representing 23 soils reported in the literature also showed good agreement between estimated and measured log10(K) values with ME of −0.01, RE of 9.5%, RMSE of 0.77 and R2 of 0.85. The new K(θ, ψ) model outperformed the Mualem‐van Genuchten model and two recently published pedo‐transfer functions. The new K(θ, ψ) model can be applied for estimating K under field conditions and for hydrologic modeling without need for soil water retention curve data fitting to derive a K function. Key Points A new unsaturated hydraulic conductivity model was developed in terms of independent θ and ψ values Best fitting values of two parameters in the new unsaturated hydraulic conductivity model were determined from 150 soils in the calibration data set The new model provided reliable estimates of hydraulic conductivity for 72 soils from two independent data sets</description><subject>capillary bundle model</subject><subject>Cementation</subject><subject>Curve fitting</subject><subject>Datasets</subject><subject>Electrical conductivity</subject><subject>Electrical resistivity</subject><subject>Hydraulic conductivity</subject><subject>hydraulic conductivity model</subject><subject>Hydraulics</subject><subject>Hydrologic models</subject><subject>Hydrology</subject><subject>Mathematical models</subject><subject>matric potential</subject><subject>Modelling</subject><subject>Moisture content</subject><subject>Parameters</subject><subject>Pore size</subject><subject>Pore size distribution</subject><subject>Root-mean-square errors</subject><subject>Salinity</subject><subject>Saturation</subject><subject>Size distribution</subject><subject>Soil</subject><subject>Soil water</subject><subject>Tortuosity</subject><subject>Transfer functions</subject><subject>Unsaturated soils</subject><subject>Water content</subject><issn>0043-1397</issn><issn>1944-7973</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp9kE1OwzAQhS0EEqWw4wCW2DZgx_Hfso2AIhUhFaouIyd2RUoaFzsBskOcgDNyEgwBiRWrWbxv5s17ABxjdIpRLM9iFMfLOSIJFmwHDLBMkohLTnbBAKGERJhIvg8OvF8jhBPK-AC8jWu4qL1qWqcao-G00061VVnA1Na6LZryqWw6eG21qeBE-YDYGjb3BqZqW1aVch2ctLWuTM-MvrWJs_bBf7y-p9aZ321Va7hULxtVB-F2Uza-Fw7B3kpV3hz9zCFYXJzfpdNodnN5lY5nkYqlYFFCtQhPF4TnuUIFlWxFKeYsx1oKziVjBTUh7YrmGDNJBUGIKKl5LJIEYUWG4KS_u3X2sTW-yda2dXWwzGIRLDClQgRq1FOFs947s8q2rtyEmBlG2VfL2d-WA056_LmsTPcvmy3n6TxmjDLyCc0rfxw</recordid><startdate>202306</startdate><enddate>202306</enddate><creator>Fu, Yongwei</creator><creator>Horton, Robert</creator><creator>Ren, Tusheng</creator><creator>Heitman, Joshua</creator><general>John Wiley &amp; Sons, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7QL</scope><scope>7T7</scope><scope>7TG</scope><scope>7U9</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H94</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>M7N</scope><scope>P64</scope><orcidid>https://orcid.org/0000-0002-8708-0693</orcidid><orcidid>https://orcid.org/0000-0002-6277-0794</orcidid></search><sort><creationdate>202306</creationdate><title>An Unsaturated Hydraulic Conductivity Model Based on the Capillary Bundle Model, the Brooks‐Corey Model and Waxman‐Smits Model</title><author>Fu, Yongwei ; Horton, Robert ; Ren, Tusheng ; Heitman, Joshua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a2986-45d8145c37bba0c596f55176b1d9877966c5e797f5b1169583003a9d7284401a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>capillary bundle model</topic><topic>Cementation</topic><topic>Curve fitting</topic><topic>Datasets</topic><topic>Electrical conductivity</topic><topic>Electrical resistivity</topic><topic>Hydraulic conductivity</topic><topic>hydraulic conductivity model</topic><topic>Hydraulics</topic><topic>Hydrologic models</topic><topic>Hydrology</topic><topic>Mathematical models</topic><topic>matric potential</topic><topic>Modelling</topic><topic>Moisture content</topic><topic>Parameters</topic><topic>Pore size</topic><topic>Pore size distribution</topic><topic>Root-mean-square errors</topic><topic>Salinity</topic><topic>Saturation</topic><topic>Size distribution</topic><topic>Soil</topic><topic>Soil water</topic><topic>Tortuosity</topic><topic>Transfer functions</topic><topic>Unsaturated soils</topic><topic>Water content</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fu, Yongwei</creatorcontrib><creatorcontrib>Horton, Robert</creatorcontrib><creatorcontrib>Ren, Tusheng</creatorcontrib><creatorcontrib>Heitman, Joshua</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Meteorological &amp; 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Here we first develop a theoretical hydraulic‐electrical conductivity (σ) relationship under low and high salinity cases based on the capillary bundle model and Waxman and Smits model which can account for the non‐linear behavior of σ at low salinities. Then the K‐σ relationship is converted into a K(θ, ψ) model using the Brooks‐Corey model. The model includes two parameters c and γ. Parameter c accounts for the variation of the term (λ + 2)/(λ + 4) where λ is the pore size distribution parameter in the Brooks‐Corey model, and the term m‐n where m and n are Archie's saturation and cementation exponents, respectively. Parameter γ is the sum of the tortuosity factor accounting for the differences between hydraulic and electrical tortuosity and Archie's saturation exponent. Based on a calibration data set of 150 soils selected from the UNSODA database, the best fitting log(c) and γ values were determined as −2.53 and 1.92, −4.39 and −0.14, −5.01 and −1.34, and −5.79 and −2.27 for four textural groups. The estimated log10(K) values with the new K(θ, ψ) model compared well to the measured values from an independent data set of 49 soils selected from the UNSODA database, with mean error (ME), relative error (RE), root mean square error (RMSE) and coefficient of determination (R2) values of 0.02, 8.8%, 0.80 and 0.73, respectively. A second test of the new K(θ, ψ) model using a data set representing 23 soils reported in the literature also showed good agreement between estimated and measured log10(K) values with ME of −0.01, RE of 9.5%, RMSE of 0.77 and R2 of 0.85. The new K(θ, ψ) model outperformed the Mualem‐van Genuchten model and two recently published pedo‐transfer functions. The new K(θ, ψ) model can be applied for estimating K under field conditions and for hydrologic modeling without need for soil water retention curve data fitting to derive a K function. Key Points A new unsaturated hydraulic conductivity model was developed in terms of independent θ and ψ values Best fitting values of two parameters in the new unsaturated hydraulic conductivity model were determined from 150 soils in the calibration data set The new model provided reliable estimates of hydraulic conductivity for 72 soils from two independent data sets</abstract><cop>Washington</cop><pub>John Wiley &amp; Sons, Inc</pub><doi>10.1029/2022WR034186</doi><tpages>25</tpages><orcidid>https://orcid.org/0000-0002-8708-0693</orcidid><orcidid>https://orcid.org/0000-0002-6277-0794</orcidid><oa>free_for_read</oa></addata></record>
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subjects capillary bundle model
Cementation
Curve fitting
Datasets
Electrical conductivity
Electrical resistivity
Hydraulic conductivity
hydraulic conductivity model
Hydraulics
Hydrologic models
Hydrology
Mathematical models
matric potential
Modelling
Moisture content
Parameters
Pore size
Pore size distribution
Root-mean-square errors
Salinity
Saturation
Size distribution
Soil
Soil water
Tortuosity
Transfer functions
Unsaturated soils
Water content
title An Unsaturated Hydraulic Conductivity Model Based on the Capillary Bundle Model, the Brooks‐Corey Model and Waxman‐Smits Model
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